How Artificial Intelligence (AI) and Machine Learning (ML) Drive Cyber Security in FinTech?
Just like most other industries fintech companies are also increasingly relying on cutting-edge technologies for delivering their services in an engaging and audience-centric manner.
In recent years, fintech solutions are particularly depending on artificial intelligence (AI) and machine learning (ML) for strategic decision making, garnering customer insights and making the digital transaction experience better.
Both AI and ML have the potential to simplify the transactions and overall customer experience to a great extent. Apart from enhancing the customer experience, these two technologies are also playing a great role in strengthening security and preventing vulnerabilities through preemptive steps and measures. Apart from this, it helps to understand consumer buying behavior.
Before you hire a mobile app development company for your next fintech app project, it is important to understand these two cutting-edge technologies and their role in enhancing security. Here we are going to explain some of the key areas where this impact is particularly visible.
AI to differentiate and detect unsolicited access
For the fintech industry addressing security concerns happens to be the topmost priority and hence leading fintech apps leave no stone unturned when it comes to solving security issues. AI-based security solutions are becoming trendy for fintech apps for their precise ability to nab threats right at the budding stage.
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Like any machine language AI is also value-agnostic and cannot differentiate between good and fishy transactions. Just because the login process and the underlying conditions remain the same for any transaction, it becomes hard to detect an attempt or a real transaction with the wrong intent.
But the same system trained with a Machine learning algorithm can just detect the anomalies, deviations, or irregularities to trigger that something fishy is going on under the cover. Instead of taking instant judgments on the transactions, AI and ML can just take note of anomalies and irregularities that can trigger some bigger threats.
Administering the Access Control
Most of the cybersecurity threats originate from the less regulated access control mechanism and this is exactly where AI can really play a great role. The principal objective of cybercriminals and hackers is to break the access control mechanism so that they can roam around freely and steal information for their own malicious purposes.
Access control is aimed at preventing identity theft. Naturally, preventing unauthorized access is regarded as the most important defense mechanism for Fintech companies. AI-powered e-signatures combined with biometric authorization can make a huge difference when it comes to preventing identity theft.
To securely store credentials, passwords, admin and service accounts, keys, and certificates, you should consider using an encrypted enterprise password vault. This will enable you to share access to internal, external, or remote resources without disclosing credentials.
AI chatbots helping with data-driven insights
These days in fintech apps, intelligent AI-powered chatbots are also garnering huge traction. Chatbots apart from communicating with customers with real-time suggestions and help on different financial products and information, are also playing a great role in helping customers to find the solutions they need.
Thanks to intelligent chatbots fintech companies can offer personalized product suggestions, portfolio recommendations, and financial planning. Both AI and machine learning technology can help a program understand customer requirements better and find solutions accordingly.
Now, apart from delivering a better customer experience with their fintech purchase and transactions, intelligent chatbots gather a lot of customer data through communication. The huge volume of customer data collected through chatbots easily helps an AI algorithm to detect irregularities and out-of-the-box scenarios triggering security concerns.
RPA to facilitate a proactive security
Process Intelligence (RPA) which is a subset of AI enjoys great scope to enhance security measures. In general, the mainstream AI has lesser scope in augmenting the security, while RPA comes with very specific capabilities to make security better.
In this respect, one must understand that modern fintech solutions already went way beyond conventional security measures in warding off security vulnerabilities and threats. This is exactly where RPA pitches in. RPA can take care of security safeguards with a whole array of iterative steps including protocol and ownership verification, monitoring and facilitating the checks and balance tools, etc.
In the banking industry where the scope of security vulnerabilities goes deeper than the so-called intelligent security checks, static AI-powered security may not be enough. Just because the threats here are all-encompassing and deeply penetrating in nature, proactive, dynamic, and always alert robotic security tools happen to be more effective.
Going beyond the defensive mindset
In spite of the fact that security challenges are really worrisome in the fintech industry, the administrators and strategists cannot be on a defensive footing. If you still feel that your system can be hacked at any point in time threatening the entire business, you lack the right attitude to deal with the ever-increasing and sophisticated security threats and vulnerabilities. Instead of echoing this threat perception, the fintech strategists must remain proactively alert and should be on the right footing in respect of best practices, measures, and tools.
One cannot help but admit that AI and ML technologies are still not all-powerful to prevent all sorts of security vulnerabilities. Cybersecurity still involves unfathomable complexities that cannot be mitigated with any technology and tool just overnight. The positive thing that security experts should remember is that over the years security practices and measures continued to garner more strength to prevent the vast majority of security threats.
It has been seen that fintech companies that are most exposed to security threats and vulnerabilities mostly adhere to the concept of a single-window solution to all kinds of security threats. In reality, there cannot be one comprehensive security tool to take care of multifaceted security threats in the fintech sector. Just like security threats, security measures, tools, and practices need to evolve over time as well.
The question is how financial firms can actually bring the advantages of AI, ML, and RPA to their fintech apps to address the major security loopholes and vulnerabilities in the most befitting manner? Well, the answer of course lies with your choice of fintech development experts with the right skills, exposure, and experience in delivering superior fintech solutions with state-of-the-art security protocols.